{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 0 - Data Exploration and Preparation\n",
    "\n",
    "## Overview\n",
    "\n",
    "Our goal is to train a deep learning model that can make steering angle predictions based on an input that comprises of camera images and the vehicle's last known state. In this notebook, we will prepare the data for our end-to-end deep learning model. Along the way, we will also make some useful observations about the dataset that will aid us when it comes time to train the model. \n",
    "\n",
    "\n",
    "## What is end-to-end deep learning?\n",
    "\n",
    "End-to-end deep learning is a modeling strategy that is a response to the success of deep neural networks. Unlike traditional methods, this strategy is not built on feature engineering. Instead, it leverages the power of deep neural networks, along with recent hardware advances (GPUs, FPGAs etc.) to harness the incredible potential of large amounts of data. It is closer to a human-like learning approach than traditional ML as it lets a neural network map raw input to direct output. A big downside to this approach is that it requires a very large amount of training data which makes it unsuitable for many common applications. Since simulators can (potentially) generate data in infinite amounts, they are a perfect data source for end-to-end deep learning algorithms. If you wish to learn more, [this video](https://www.coursera.org/learn/machine-learning-projects/lecture/k0Klk/what-is-end-to-end-deep-learning) by Andrew Ng provides a nice overview of the topic.\n",
    "\n",
    "Autonomous driving is a field that can highly benefit from the power of end-to-end deep learning. In order to achieve SAE Level 4 or 5 Autonomy, cars need to be trained on copious amounts of data (it is not uncommon for car manufacturers to collect hundreds of petabytes of data every week), something that is virtually impossible without a simulator. \n",
    "\n",
    "With photo-realistic simulators like [AirSim](https://github.com/Microsoft/AirSim), it is now possible to collect a large amount of data to train your autonomous driving models without having to use an actual car. These models can then be fine tuned using a comparably lesser amount of real-world data and used on actual cars. This technique is called Behavioral Cloning. In this tutorial, you will train a model to learn how to steer a car through a portion of the Landscape map in AirSim using only one of the front facing webcams on the car as visual input. Our strategy will be to perform some basic data analysis to get a feel for the dataset, and then train an end-to-end deep learning model to predict the correct driving control signal (in this case the steering angle) given a frame from the webcam, and the car's current state parameters (speed, steering angle, throttle etc.).\n",
    "\n",
    "Before you begin, please make sure you have the dataset for the tutorial downloaded. If you missed the instructions in the readme file, [you can download the dataset from here](https://aka.ms/AirSimTutorialDataset).\n",
    "\n",
    "Let us start by importing some standard libraries.\n",
    "\n",
    "**NOTE: If you see text within << ...... >> in some of the comments in these notebooks, it means you are expected to make a change in the accompanying code.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import h5py\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image, ImageDraw\n",
    "import os\n",
    "import Cooking\n",
    "import random\n",
    "\n",
    "# << Point this to the directory containing the raw data >>\n",
    "RAW_DATA_DIR = 'data_raw/'\n",
    "\n",
    "# << Point this to the desired output directory for the cooked (.h5) data >>\n",
    "COOKED_DATA_DIR = 'data_cooked/'\n",
    "\n",
    "# The folders to search for data under RAW_DATA_DIR\n",
    "# For example, the first folder searched will be RAW_DATA_DIR/normal_1\n",
    "DATA_FOLDERS = ['normal_1', 'normal_2', 'normal_3', 'normal_4', 'normal_5', 'normal_6', 'swerve_1', 'swerve_2', 'swerve_3']\n",
    "\n",
    "# The size of the figures in this notebook\n",
    "FIGURE_SIZE = (10,10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the raw data. There are two parts to the dataset - the images and the .tsv file. First, let us read one of the .tsv files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Speed (kmph)</th>\n",
       "      <th>Throttle</th>\n",
       "      <th>Steering</th>\n",
       "      <th>Brake</th>\n",
       "      <th>Gear</th>\n",
       "      <th>ImageName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93683464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_0.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>93689595</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_1.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_2.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_3.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_4.png</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Timestamp  Speed (kmph)  Throttle  Steering  Brake Gear  ImageName\n",
       "0   93683464             0       0.0  0.000000    0.0    N  img_0.png\n",
       "1   93689595             0       0.0  0.000000    0.0    N  img_1.png\n",
       "2   93689624             0       0.0 -0.035522    0.0    N  img_2.png\n",
       "3   93689624             0       0.0 -0.035522    0.0    N  img_3.png\n",
       "4   93689624             0       0.0 -0.035522    0.0    N  img_4.png"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_tsv_path = os.path.join(RAW_DATA_DIR, 'normal_1/airsim_rec.txt')\n",
    "sample_tsv = pd.read_csv(sample_tsv_path, sep='\\t')\n",
    "sample_tsv.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This dataset contains our label, the steering angle. It also has the name of the image taken at the time the steering angle was recorded. Let's look at a sample image - 'img_0.png' inside the 'normal_1' folder (more on our folder naming style later)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x4eb7dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_image_path = os.path.join(RAW_DATA_DIR, 'normal_1/images/img_0.png')\n",
    "sample_image = Image.open(sample_image_path)\n",
    "plt.title('Sample Image')\n",
    "plt.imshow(sample_image)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One immediate observation that we can make about this image is that **only a small portion of the image is of interest**. For example, we should be able to determine how to steer the car by just focusing on the ROI of the image shown in red below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x921ca90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_image_roi = sample_image.copy()\n",
    "\n",
    "fillcolor=(255,0,0)\n",
    "draw = ImageDraw.Draw(sample_image_roi)\n",
    "points = [(1,76), (1,135), (255,135), (255,76)]\n",
    "for i in range(0, len(points), 1):\n",
    "    draw.line([points[i], points[(i+1)%len(points)]], fill=fillcolor, width=3)\n",
    "del draw\n",
    "\n",
    "plt.title('Image with sample ROI')\n",
    "plt.imshow(sample_image_roi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Extracting this ROI will both reduce the training time and the amount of data needed to train the model**. It will also prevent the model from getting confused by focusing on irrelevant features in the environment (e.g. mountains, trees, etc)\n",
    "\n",
    "Another observation we can make is that **the dataset exhibits a vertical flip tolerance**. That is, we get a valid data point if we flip the image around the Y axis if we also flip the sign of the steering angle. This is important as it effectively doubles the number of data points we have available. \n",
    "\n",
    "Additionally, **the trained model should be invariant to changes in lighting conditions**, so we can generate additional data points by globally scaling the brightness of the image.\n",
    "\n",
    "\n",
    "> **Thought Exercise 0.1:** \n",
    "Once you are finished with the tutorial, as an exercise, you should try working with the dataset provided without modifying it using one or more of the 3 changes described above, keeping everything else the same. Do you experience vastly different results? \n",
    "\n",
    "\n",
    "\n",
    "> **Thought Exercise 0.2:**\n",
    "We mentioned in the Readme that end-to-end deep learning eliminates the need for manual feature engineering before feeding the data to the learning algorithm. Would you consider making these pre-processing changes to the dataset as engineered features? Why or why not? \n",
    "\n",
    "\n",
    "Now, let's aggregate all the non-image data into a single dataframe to get some more insights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of data points: 46738\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Speed (kmph)</th>\n",
       "      <th>Throttle</th>\n",
       "      <th>Steering</th>\n",
       "      <th>Brake</th>\n",
       "      <th>Gear</th>\n",
       "      <th>ImageName</th>\n",
       "      <th>Folder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93683464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_0.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>93689595</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_1.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_2.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_3.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_4.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Timestamp  Speed (kmph)  Throttle  Steering  Brake Gear  ImageName  \\\n",
       "0   93683464             0       0.0  0.000000    0.0    N  img_0.png   \n",
       "1   93689595             0       0.0  0.000000    0.0    N  img_1.png   \n",
       "2   93689624             0       0.0 -0.035522    0.0    N  img_2.png   \n",
       "3   93689624             0       0.0 -0.035522    0.0    N  img_3.png   \n",
       "4   93689624             0       0.0 -0.035522    0.0    N  img_4.png   \n",
       "\n",
       "              Folder  \n",
       "0  data_raw/normal_1  \n",
       "1  data_raw/normal_1  \n",
       "2  data_raw/normal_1  \n",
       "3  data_raw/normal_1  \n",
       "4  data_raw/normal_1  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_path_raw_folders = [os.path.join(RAW_DATA_DIR, f) for f in DATA_FOLDERS]\n",
    "\n",
    "dataframes = []\n",
    "for folder in full_path_raw_folders:\n",
    "    current_dataframe = pd.read_csv(os.path.join(folder, 'airsim_rec.txt'), sep='\\t')\n",
    "    current_dataframe['Folder'] = folder\n",
    "    dataframes.append(current_dataframe)\n",
    "    \n",
    "dataset = pd.concat(dataframes, axis=0)\n",
    "\n",
    "print('Number of data points: {0}'.format(dataset.shape[0]))\n",
    "\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now address the naming of the dataset folders. You will notice that we have two types of folders in our dataset - 'normal', and 'swerve'. These names refer to two different driving strategies. Let's begin by attempting to get an understanding of the differences between these two styles of driving. First, we'll plot a portion of datapoints from each of the driving styles against each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x92a9358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "min_index = 100\n",
    "max_index = 1100\n",
    "steering_angles_normal_1 = dataset[dataset['Folder'].apply(lambda v: 'normal_1' in v)]['Steering'][min_index:max_index]\n",
    "steering_angles_swerve_1 = dataset[dataset['Folder'].apply(lambda v: 'swerve_1' in v)]['Steering'][min_index:max_index]\n",
    "\n",
    "plot_index = [i for i in range(min_index, max_index, 1)]\n",
    "\n",
    "fig = plt.figure(figsize=FIGURE_SIZE)\n",
    "ax1 = fig.add_subplot(111)\n",
    "\n",
    "ax1.scatter(plot_index, steering_angles_normal_1, c='b', marker='o', label='normal_1')\n",
    "ax1.scatter(plot_index, steering_angles_swerve_1, c='r', marker='o', label='swerve_1')\n",
    "plt.legend(loc='upper left');\n",
    "plt.title('Steering Angles for normal_1 and swerve_1 runs')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Steering Angle')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can observe a clear difference between the two driving strategies here. The blue points show the normal driving strategy, which as you would expect, keeps your steering angle close to zero more or less, which makes your car mostly go straight on the road. \n",
    "\n",
    "The swerving driving strategy has the car almost oscillating side to side across the road. This illustrates a very important thing to keep in mind while training end-to-end deep learning models. Since we are not doing any feature engineering, our model relies almost entirely on the dataset to provide it with all the necessary information it would need during recall. Hence, to account for any sharp turns the model might encounter, and to give it the ability to correct itself if it starts to go off the road, we need to provide it with enough such examples while training. Hence, we created these extra datasets to focus on those scenarios. Once you are done with the tutorial, you can try re-running everything using only the 'normal' dataset and watch your car fail to keep on the road for an extended period of time.\n",
    "\n",
    "> **Thought Exercise 0.3:**\n",
    "What other such data collection techniques do you think might be necessary for this steering angle prediction scenario? What about autonomous driving in general?\n",
    "\n",
    "Now, let us take a look at the number of datapoints in each category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lys4MFaDnRI6jxreYdCrth8Dv3PmjNLUsQ9IUKZQqO5EWoNdjAdL0WcJQMfpttVzsi5xHaniWIWkjFEqV+cAJwJtI9wAtzaQa6cLrr1fLxetih5EalWVImoRCqXIg8HbgtUB75DgSwN+ArwMXVMvFWuwwUiOxDEkTVChVOoGjgbeRHgNMqkcrgIuAr1XLxWtih5EagWVIWo9sMfTbgDcDm8dNI22Qm4GzgfOr5eKK2GGkemUZkkZRKFVagaNIS9DhuDdoNbYngXOBL1fLxXtjh5HqjWVIGqZQqiwATgbeAvxL5DjSVBsEKsAXquXi72KHkeqFZUgCCqXKfsCppPsFmh05jjQTbgfOBL7tfouUd5Yh5VqhVNkf+BjwkthZpEjuAz4NfMtSpLyyDCmXCqXK80hL0EtjZ5HqhKVIuWUZUq4USpV9SUvQy2JnkeqUpUi5YxlSLhRKleeSlqCjYmeRGoSlSLlhGVJTK5QqewPdwCsiR5EalaVITc8ypKZUKFX2Ii1Br4wcRWoWliI1LcuQmkqhVNmTtAS9CneUKE2H+4BPAedWy8WB2GGkqWAZUlPIjh5/OukhMyxB0vS7BXhHtVy8MnYQaWNZhtTQssNmvA34OB43TIrh+8Bp1XJxYewg0mRZhtSwCqXKwcCXgOfEziLl3DLgE8CZridSI7IMqeEUSpWnAf8LHBc7i6S1/B14Z7Vc/G3sINKGsAypYRRKlTbgnaQLpDeNm0bSOC4G3lMtF++LHUSaCMuQGkKhVDmUdEps99hZJE3ISqAM/G+1XOyJHUYaj2VIda1QqmwLfA54Y+wskiblHtJRop/HDiKNxTKkulQoVWYB7wY+AsyNHEfSxvsl8K5quXh37CDSSJYh1Z3siPLfBnaLnUXSlOoFPgicUS0XffNR3bAMqW5k+wz6IPBhoC1yHEnT5zLg+Gq5+EDsIBJYhlQnCqXKTsD5wAGxs0iaETXSPVhfEDuIZBlSdIVS5RTgTKArdhZJM+4i4K3VcvHJ2EGUX5YhRZMdT+wbwCtiZ5EU1ULghGq5eGnsIMony9AUCyEkwBlJkrwv+/40YG6SJN0zmOE84JIkSX40U/e5oQqlylHAN4EFsbNIqgsJ8GXg/dVycWXsMMqXltgBmlAv8JoQwlaTuXIIoakXDhdKla5CqfJV4BdYhCQNCcA7gBsLpco+scMoX5r6jTeSVcDXgPeQbhm1Rgjh6cC5wHxgEXBCkiT3ZyM5i4G9gRtDCE8B/wpsA+wCvJd0YfFLgYeAlydJ0h9C+AjwcqADuBp4S1LHQ32FUmV/0kXSO8fOIqluPRO4plCqfAL4dLVcHIgdSM3PkaHp8WXgmBDCZiNO/xLwnSRJ9gS+C3xh2Hm7AIetnl4DdgSKwCuBC4DLkiTZg3QX98XVt5ckyfOSJNmdtBAdNS0/zUYqlCpthVKlG/gTFiFJ6zcL+Djwp2xLU2laWYamQZIkS4HvAKeOOOtA4HvZ/88HDh523g+TJBn+CehXSZL0A7cArcCvs9NvAQrZ/18YQrguhHAL8CLg2VP2Q0yRQqlSIC1BH8WRSEkb5gDgpkKp4uF4NK0sQ9PnLOAkxt9cfPiU1vIR5/UCJEkyCPQPm/4aBNpCCHOAs4HXZiNGXwfmTEXwqVIoVV4AXA/sHzmKpMbVBXy/UKqcXihVfM/StPCJNU2SJFlMuv+Mk4adfDVDBxw9hnTEZLJWF5/HQwhzgdduxG1NuUKp8g7gt8CkFpJL0gjvBy4plCqbxw6i5mMZml6fY+0ycCpwQgjhZuA44F2TveEkSZaQjgbdAvyUdAQmukKpMrtQqnwd+CJOi0maWi8F/lwoVTxuoaaU+xnSlCmUKlsDPwYOip1FUlNbChxXLRd/HjuImoNlSFMi2y/IT4HtY2eRlAsJ6YYZn6yWi76RaaNYhrTRCqXK0aSH1eiInUVS7vwYOL5aLo7cCEWaMMuQJi3bsqMM/FfsLJJy7RbgldVy8d7YQdSYLEOalGyLju+RLmiUpNgWA6+vlou/jx1EjcetybTBCqXKrsB1WIQk1Y8tgN8USpX3xA6ixuPIkDZIoVR5KfB9YOShRiSpXpwL/IfHNdNEOTKkCSuUKm8mPdq8RUhSPTsR+GGhVGmPHUSNwTKkCSmUKqeRftpqjZ1Fkibg1aR7rB7vkEgS4DSZJqBQqpxOuit8SWo01wDFarn4ZOwgql+WIY2pUKq0Al8BTo6dRZI2ws3AEdVy8dHYQVSfLEMaVTbX/j3gNbGzSNIUuAs4rFou3h87iOqPZUjryObYfwa8OHYWSZpCDwCHV8vFv8cOovpiGdJaCqXKJsAvgYNjZ5GkabAIeEm1XPxr7CCqH25NpjWyvUr/FouQpOY1H7isUKr4Oqc1LEMCoFCqbAX8Adg/dhZJmmabAZcWSpUjYwdRfbAMiUKpsjVwObB35CiSNFM6gJ8XSpXXxQ6i+CxDOVcoVbYDrgCeHTuLJM2wWcAPCqXKsbGDKC4XUOdYoVTZEvgT8MzYWSQpolXAq6vl4iWxgygOy1BOZZvP/wHYL3YWSaoDK0m3Mvtj7CCaeU6T5VChVJkN/ASLkCSt1gH8olCqPCd2EM08y1DOFEqVFuDbwBGxs0hSndkM+E2hVNkpdhDNLMtQ/nweeGPsEJJUp7Ym3ex+m9hBNHMsQzlSKFU+Arwjdg5JqnP/SjpCNC92EM0MF1DnRKFU+U/g7Ng5JKmBXE16LLMVsYNoelmGciDbqdgPcCRQkjbUr4BXVsvF/thBNH18c2xyhVLlMOAC/F1L0mS8FPh2oVQJsYNo+vgG2cQKpcq+wMXA7NhZJKmBvQn4QuwQmj6WoSZVKFV2JR3enRs7iyQ1gXcUSpXu2CE0PVwz1IQKpcq2pAv/nh47iyQ1mZOq5eK5sUNoalmGmkyhVGkHrsS9S0vSdOgFDqmWi9fHDqKp4zRZ8/kiFiFJmi7twI8Lpcr82EE0dSxDTaRQqpwMnBI7hyQ1uR2AiwqlSlvsIJoalqEmUShVngd8KXYOScqJFwD/FzuEpoZrhppANlx7A+mnFUnSzDm2Wi5+N3YIbRzLUIMrlCqtwKXAi2JnkaQcWgn8W7VcvCl2EE2e02SNr4xFSJJi6QB+UihVtogdRJPnyFADy445dlHsHJIkLgVeWi0XB2MH0YZzZKhBFUqVZwPu+EuS6sMRwKdjh9DkODLUgAqlyqbA9cAusbNIktbyumq5+KPYIbRhHBlqMNmRk7+DRUiS6tG3spF7NRDLUOP5IPDK2CEkSaOaC1xcKFU2ix1EE2cZaiCFUuXFwMdi55AkjWtn4MuxQ2jiXDPUILJ1QrfijhUlqVG8sVouXhg7hNbPkaHGcSYWIUlqJOcUSpXtYofQ+lmGGkChVHkZcGLsHJKkDTIPOC/b8EV1zDJU5wqlyjzg67FzSJIm5TDg1NghND7LUP37ArBt7BCSpEkru7l9fXMBdR0rlCqvAi6OnUOStNH+CuxfLRf7YwfRuhwZqlOFUmUr4Kuxc0iSpsTewH/HDqHRWYbq19nAgtghJElT5kOFUmWP2CG0LstQHSqUKm8AXhc7hyRpSs0iPVxHW+wgWptlqM4USpWtcc+lktSs9gHeHzuE1mYZqj9fA7aMHUKSNG0+UihVnhU7hIZYhupIoVQ5DnhF7BySpGnVTjpd1ho7iFKWoTpRKFW2Id2nkCSp+e0HvD12CKUsQ/WjDGweO4QkacZ0F0oVl0XUActQHSiUKvsBx8XOIUmaUfOAT8QOIctQvTgL8EB+kpQ//+G+h+KzDEVWKFXeBBwYO4ckKYpW0g/Eishjk0VUKFU6gTuBHWJnkSRF9epqufjT2CHyypGhuP4Li5AkCT5bKFXaY4fIK8tQJIVSZXvcC6kkKbUj8O7YIfLKMhRPGeiMHUKSVDc+WChVnhY7RB5ZhiIolCoHAEfHziFJqiubAJ+OHSKPXEA9wwqlSgCuAfaPnUWSVHcSYL9qufiX2EHyxJGhmXcMFiFJ0ugCbmo/4xwZmkHZpvR/B7aPnUWSVNeOrpaL348dIi8cGZpZH8AiJElav9OzD9CaAZahGVIoVbYl3a+QJEnrswPwttgh8sIyNHNOAzpih5AkNYz3FUqVObFD5EFb7AB5UChVtgL+I3aO2PqfeJBFPz99zferljzC5gcfy6bPe+Wa02rX/YQll5/L9u/8Lq2dm416O4O9K1j4jbfSucuBbHH4fwKw/I4rqV1zEQwO0rHjvsx74YkALL3hFyy76Ve0bjqfBa/5EKF1Fj0P3saKv1/NFi8+Zb2ZkyTh0R98MLtuG4987wMkq/phcJDOXQ9i80OOWevyi3/7FZbd8jv+5b0/Sn/GpY/xeOVMBnuWQzLIvEOPp2PH5zGwcimLfvoZ+h6+i7l7vHjNzwHw6EUfYWDZYhgcpH2HZ7HF4f9JaGnlyT98kzk77kvH058zwUdcUoN7GnAS8OXYQZqdI0Mz411AV+wQsc3acnu2PeGLbHvCF9nm+LMIs9rp3GXoGLWrli6ip/pXWjedP+7tLPnj+bTvMHSQ54GVS3nysm+x9Rs/xbYnn83AiiWsrN4EwLK//YZtTvwSs7fekZX33kiSJNSu+gGbHfSmCWVeec9fmL3gX2lp74TWWWz9xk+z7YlfYpsTvsDKe2+g96E711y29+G7GOxdvtb1a1dfSNczD2HbE77AVq94P09ceg4AoXU2mx9y7JrSNtz8V5bS+zjpywyuWMqKO/8EwCb7vJyl1/5oQrklNY33F0qVWbFDNDvL0DQrlCqbAu+InaPe9Nz3N2Ztvg1tmy1Yc9qTv/868154AumWpaPrfeRuBpYvoeNf915z2qoljzBri23XjCTNefperPjH1UNXGhgg6e8ltLSx/LY/0LHjvrTOmTuhnMtvu5zOndM9IYQQaJmdznQmg6tgcABCyL4f4MnLz2XzF5ww4hYCg70r0sv0Lqdt7hYAtMyew5ztn01om73Ofba0Z2smBwdIBvrX3EfbZgsYXLmUgWVPTii7pKbwL8CxsUM0O8vQ9HsbsHnsEPVm+R1X0rnb89d8v+Ku62jdZEtmL3jGmNdJkkGe/MM31hlNaZu3Lf1PPMiq2qMkgwOsvOtaBpYuAmDT/V7Dw+e/j8EVNdq3243lt/6eTfYuTjhn70O3M3vrnYYyDA6w8Fvv5MEvHsucwl60b7srAE/deAmdO+2/puysttnBR7P8tst48MvH89gPu5l3+FsndL+PXvhhHvziMYTZnXTuetCa02dvvSM9D90+4fySmkKpUKr4fj2NXDM0jQqlSgfwntg56k0y0M/Ku//MvEOPB2Cwv4faNRey9Rs+Me71nrqxQseO+9I2Yhqtdc5ctnjJ21j0s9MhBNq3241VSx4BYO7uL2Lu7i8CYMmfvscm+7yClffcwPJbf0/rpvOZ96KTCGHs15jBnmVDIzVAaGll2xO+yGDPMh67+FP0LarSMmcTVtx5FVsf/Zl1rr/i9iuYu8eL2XS/19D70B08ccnn2OakL497nwBbv+ETJKv6ePwXn6XnvpvXjIS1dG2erieSlCe7AK8HfhA7SLOyaU6vk4EF671Uzqy85wZmb70jrV3zgHSaa1XtURae+04ePOdEBp56nIfPe/c600G9C+/kqRsqPHjOiTx52bksu/UPPHn5eQB07rQ/2/y/M9jmuM8xa4vtmTVv27Wuu+qpJ+h75C46dz6A2jU/YKtXfiBdTF3927hZQ2ghSQbXOb1lzlzm7LAHK++5kb7H7qF/yUIe+uopPHjOiST9vTz01XRx9rKbf0vnMw8BoH273UhW9TG4YumEHqfQNpuOnfZn5d3XrjktWdU36tSapKb3P9nhnDQNHBmaJtmCN/crNIrlt19B17ApstnzC+zwzu+u+f7Bc05km+PPXGdrsvkvH3o4l93yO/oeuYt5L3gzAAPLl9DatTkDPct46q8V5r+ytNZ1l/zxAjY/JJ12T/r70nU4IZCs6h03a9sW26drkuZty8CKGqGllZY5cxns76XnvpvYdP/X0rnj8+h8xwVrrnP/Ga9lu7d8HYDWTefTc9/fmLvHYfQ//gDJQD8tY2wlBzDYt5LBvpW0zd0infK75y+0b/+sNeevWvwQXbsePG5mSU1pD+ASYFgjAAAgAElEQVTlwM9jB2lGlqHp8/9Id5qlYQb7e+ip3sSWR05sTXnvw3ex7KZfseVLTx33cot//zX6H7sXgM3+7Y3M2mK7Nef1PfpPIF1vAzB3zyN4+JvvoHXTrdj8oKPHvd2OHfel5/5b0jK0bDGPV86EZBCSQTqfeQidO+037vXnvegkFv/6iyy9/qcQAlu+7N2EbEH0g+ecSNK3gmRgFSv+cS0L3vAJWjs2YdGPP5EunB4cZM7T92STvV8GQDKwiv4nH2b2NjuPe5+SmtYHsQxNC49NNg0KpUorcAfgu1aDW7VsMU9ccgZbv/GTsaOw4h9X0/fIP9n8+cfFjiIpnsOr5eLvYodoNq4Zmh6vwyLUFNrmbsHc57xkzebxMSWDg2y636tjx5AU14diB2hGjgxNsWyB203AnrGzSJKa0sHVcvGq2CGaiSNDU+8oLEKSpOnzwdgBmo1laOr9d+wAkqSm9tJCqeKH7ilkGZpChVJlX+DA9V5QkqSNk/uDf08ly9DUOjl2AElSLhyTHeVAU8AyNEUKpUonMLFDoUuStHE2J91yWVPAMjR1XgdsGjuEJCk3nI2YIpahqeOTUpI0kw4plCq7xg7RDCxDUyB7MnrAKEnSTPOD+BSwDE0Nn4ySpBiOzw4Mro1gGdpI2ZPw/8XOIUnKpfnAK2OHaHSWoY33CmBB7BCSpNw6JXaARmcZ2nhOkUmSYjqsUKo8PXaIRmYZ2giFUmUH4IjYOSRJudYCnBQ7RCOzDG2cE/AxlCTFd0KhVGmNHaJR+UY+SYVSpQU4MXYOSZKA7YEjY4doVJahyTsMcI5WklQvXEg9SZahyXNUSJJUT4qFUmWL2CEakWVoEgqlyhzgqNg5JEkapg3fmybFMjQ5Lwa6YoeQJGkEd8A4CZahyfHJJkmqRy/JZi+0ASxDG6hQqgQchpQk1acu0tkLbQDL0IbbD9gmdghJksbg7MUGsgxtuFfEDiBJ0jhens1iaIIsQxvOMiRJqmdPA/aPHaKRWIY2QKFUeQawe+wckiSth1NlG8AytGEcFZIkNQLL0AawDG0Yn1ySpEawW6FU2Tl2iEZhGZqgQqkyDzg4dg5JkibID/ATZBmauCLprs4lSWoEr4odoFFYhibO9UKSpEZyYKFUWRA7RCOwDE1AoVSZDRwZO4ckSRugBY+YMCGWoYl5AbBJ7BCSJG0gy9AEWIYm5ojYASRJmoSDYgdoBJahiTkkdgBJkiZhgZvYr59laD0KpUoX8NzYOSRJmqR/ix2g3lmG1u9A3KRektS4nCpbD8vQ+jlFJklqZJah9bAMrZ9lSJLUyHbLjqKgMViGxlEoVWYBB8TOIUnSRgikSz40BsvQ+PYBOmKHkCRpIzlVNg7L0Phs0pKkZuAWZeOwDI1vv9gBJEmaAvsVShW3jB6DZWh8+8cOIEnSFOgE9o4dol5ZhsZQKFXmA/8aO4ckSVPEqbIxWIbG5hSZJKmZuIh6DJahsVmGJEnNxJGhMViGxuZ6IUlSM9muUKo8PXaIemQZGtu+sQNIkjTFnhM7QD2yDI2iUKosALaMnUOSpCm2a+wA9cgyNLpdYgeQJGka+P42CsvQ6HyySJKakSNDo7AMjc4yJElqRpahUViGRrdz7ACSJE2DBYVSZfPYIeqNZWh0jgxJkpqVo0MjWIZGKJQqAdgpdg5JkqaJH/hHsAyt61+AObFDSJI0TRwZGsEytC4bsySpmVmGRrAMrcsyJElqZpahESxD63JLMklSM9u5UKr4/j+MD8a6HBmSJDWzOaTrY5WxDK3LMiRJana+1w1jGRqmUKrMAgqxc0iSNM1cNzSMZWhtOwKtsUNIkjTNHBkaxjK0tn+NHUCSpBmwdewA9cQytLb5sQNIkjQDtowdoJ5Yhta2RewAkiTNAMvQMJahtfnkkCTlwVaxA9QTy9DaHBmSJOWBH/6HsQytzSeHJCkP5hRKlc7YIeqFZWhtjgxJkvLCqbKMZWhtliFJUl44G5KxDK3NJ4YkKS8cGcpYhtbmyJAkKS8cAMhYhjKFUqUN2DR2DkmSZohlKGMZGuKokCQpT5wmy1iGhliGJEl54shQxjI0xCeFJClPfN/LWIaGODIkScoTp8kylqEhNmRJUp7Mix2gXliGhsyNHUCSpBk0K3aAemEZkiQpn1pjB6gXlqEhSewAkiTNIMtQxjI0xDIkScqTttgB6oVlSJKkfHJkKGMZGuLIkCQpTyxDGcvQEMuQJClPLEMZ5wuHWIakCHYN9997atvF98fOIeVNP201KMaOURcsQ0MsQ1IEB7bc/kix9bpDY+eQcujB2AHqhdNkQyxDUgRd9AzEziDl1GDsAPXCMiQpqq7Q4wcRKQ7LUMYyNMQXZCmCLnp8QZbi8G8vYxkaYhmSIuikJ3YEKa+cos5YhoZYhqQIOkOvf3tSHH4SyViGhviCLEXQSU+InUHKqadiB6gXliFJUXWEvtgRpLyyDGUsQ0NWxA4g5VEHvb4OSXFYhjK+CA15InYAKY/m0OfrkBTH0tgB6oUvQkMejx1AyqN2+j0+khSHI0MZy9AQy5AUwezQ7+uQFIdlKOOL0BDLkBTBbFbNip1ByinLUMYylKmWiz3A8tg5pLyZxSqnyaQ4LEMZy9DaHB2SZlgbA7NjZ5ByyjKUsQytzTIkzbBWBp0mk+KwDGUsQ2uzDEkzrJVBR4akOB6LHaBeWIbWZhmSZliLZUiKZWHsAPXCMrQ2y5A0wwLJnNgZpBxKsAytYRlam2VImmEB2mNnkHLocbpr/bFD1AvL0NosQ9KMSggBR4akmfdQ7AD1xDK0NsuQNIPa6e+JnUHKKafIhrEMrc0yJM2gOfT1xs4g5ZQjQ8NYhta2KHYAKU866HNkSIrDkaFhLENruz92AClPOkJvX+wMUk45MjSMZWiYarn4FLZlacZ0YBmSIvG9bhjL0LrujB1Ayosuety0V4rDkaFhLEPr+nvsAFJeOE0mRZEAd8UOUU8sQ+uyDEkzpIuegdgZpBx6iO7a8tgh6ollaF1Ok0kzpCs4TSZF4PvcCJahdTkyJM2QLnoGY2eQcsj3uREsQ+u6D1gZO4SUB06TSVE4MjSCZWiEarnowjJphnQFR4akCCxDI1iGRucTRZoBnU6TSTH4HjeCZWh0zqdKM6ALj8YhzbBluI+hdViGRmcZkmZAZ+hJYmeQcuYfdNf8uxvBMjQ6hxClGdBJb4idQcoZ399GYRkanSND0gzooDd2BClvbo8doB5ZhkZRLRedU5VmQEfo8zVImll/iR2gHvlCNLY7YgeQmt0c+pwmk2bW9bED1CPL0NiujR1Aanbt9LfGziDlyD/pri2OHaIeWYbGdlXsAFKzmx0sQ9IMclRoDJahsV0DuEM4aRrNZlVb7AxSjvw5doB6ZRkaQ7VcrAG3xs4hNbNZliFpJjkyNAbL0PicKpOmURsDs2JnkHJiALgxdoh6ZRkan2VImkaWIWnG3EZ3bUXsEPXKMjQ+y5A0jVoZnB07g5QTTpGNwzI0jmq5WMWdL0rTpsUyJM0UF0+PwzK0fo4OSdMkkMyJnUHKCd/LxmEZWj+fQNI0CdAeO4OUA4/QXbstdoh6ZhlaP8uQNH0cGZKm3x9iB6h3lqH1uwlYFjuE1Gxm098bAh6bTJp+v48doN5ZhtajWi4OANfFziE1mzn09sbOIOXE72IHqHeWoYlxqkyaYh309cTOIOXA3XTX7o8dot5ZhibGMiRNsY7Q2xc7g5QDTpFNgGVoYv4ErIwdQmomHfQ5TSZNP6fIJsAyNAHVcnEFPqGkKdVJT3/sDFKTS4DLYodoBJahiftp7ABSM+kMvZYhaXrdRHftidghGoFlaOJ+TnrUX0lToIueVbEzSE3OGY0JsgxNULVcfBy4OnYOqVlYhqRp97PYARqFZWjDOFUmTZGu0ONIqzR9HgWuiR2iUViGNowtW5oinViGpGn0M7prg7FDNArL0Aaolov/BG6NnUNqBnPDSl+openzk9gBGollaMM5VSZNgU56LUPS9KjhwVk3iGVow1mGpCnQhUfjkKZJhe6au67YAJahDVQtF28AHoidQ2p0naEniZ1BalJOkW0gy9DkuJBa2kid9IbYGaQm1AP8OnaIRmMZmhynyqSN1IGHJpOmwaV015bHDtFoLEOTcwWwJHYIqZF1hD5ff6Sp5xTZJPhiNAnVcnEVUImdQ2pkc+hzmkyaWj24jGNSLEOT98PYAaRG1k5fa+wMUpP5Kd01Zy0mwTI0eb8EHosdQmpU7aHfMiRNrfNiB2hUlqFJqpaL/cAFsXNIjWo2q9piZ5CayEPAb2OHaFSWoY1zbuwAUqOaxSpHhqSpc77HIps8y9BGqJaLtwF/jp1DakRtDMyKnUFqIufFDtDILEMb71uxA0iNyDIkTZlr6K79PXaIRmYZ2njfB1bGDiE1mhYG22NnkJrEebEDNDrL0Eaqlos14Mexc0iNppXEkSFp460ELowdotFZhqbG12IHkBpNYHBO7AxSE/gp3bVa7BCNzjI0Barl4h+BW2PnkBpJAKfJpI33jdgBmoFlaOp8JXYAqcE4MiRtnNvprv0hdohmYBmaOucDy2KHkBrBLFb1heDrj7SRvhQ7QLPwxWiKVMvFpcB3Y+eQGsEcentiZ5AaXA34TuwQzcIyNLXOiR1AagQd9PXGziA1uPPori2PHaJZWIamULVc/BtwTewcUr3rCL19sTNIDWwQp8imlGVo6n0+dgCp3jkyJG2UX9Bduzt2iGZiGZp6PwT+ETuEVM866emPnUFqYGfEDtBsLENTrFouDgKfiZ1DqmedTpNJk3UD3bUrY4doNpah6XEBcG/sEFK96qJnIHYGqUGdGTtAM7IMTYNqubgKOD12DqleNfM02QO1QV747eXs9uVlPPvsZXz+2qHlUd2X97DdGU+x11eWsddXlvHLu0Z/GApnPcUe56SX2fdrQ7sv++Ft/Tz77GW0fGwpf1k41Cevun8Ve56zjOd9fRl3Lx4EYElPwksuWE6SJBPK/e5f93DlfasA+NKf+9jpC08RPraUx1cMrrnMnY8PcOA3l9P+yaV89uq1l319/tpedj87/ZnPGvYz/9elPTzzS8vY85xlvPrCFSzpSfNUlwzS8amlax6Lt14ydLzrw76znCdXTix3ztwPXBQ7RDNqix2giX0L+DCwXewgUr2ZG5p3ZKitBT53xByeu00rT/Um7PO15Ry+YxvPmt8KwHsOmM1p/7b+I5FcdnwnW3Wu/Xl19wUt/OT1HbzlkrV30/S5a/r48es7qC5JOOf6Pj73kjl84ope/ufgdkII672vxSsTrn1wgLOOTHcKftAOrRy1SxcvOG/tLbe36Ah84cg5/PTOtUvcrY8N8PUb+/nzKV3MboUjL1hBcec2dt6ylcN3bOMzh7XT1hL4wG97+Mwfezn98PR+dpzXwk1vnbtOnuP2nMXZ1/fxwed7xJYRPk13rWk/SMTkyNA0qZaLfcD/xs4h1aPOJp4m22aTFp67TVp8NmkP7Da/hYeWTs0ox27zW9l1q9Z1Tp/VCitXwYr+hFmt8M/Fgzz01CCHFib2efdHt/dz5E5Dt7v3Nq0UNl/37WFBVwvP266VWSMi3LFokAO2b6VzVqCtJXDo09u4+M50lOmIHdtoa0kL2QHbt/LgU4Mjb3Ydr9h1Ft+/1ff8ER4g/ZCtaWAZml5fBx6NHUKqN10hH3Mg1SWD/PXhAfbffqg9fOnPfex5zjJO/NnKMaeCQoAjzl/BPl9bxtduWP9a8/8+uJ3/+EUPZ13Xxzv2m80H/9DDJ1448VGVqx4YYJ9t1i1ZE7X7ghauvG+AJ1YMsqI/4Zd3r+KB2rql59yb+nnpTkMF7d4lg+z91WUcet5y/phN0QHM6wj0DsATK9ZfnHLkM3TX3PBgmliGplG1XFyJm0BK6+iit2lHhlZb1pfw7xet4Kwj57Bpezoy8p/7zuafp87lprd2sc3cwPsuHf2oJFed2MWNb5nLr47p5MvX961ZyzOWvZ7WyrUnd3HZ8V3c8+Qg227SQgK84UcrOPYnK3l02fil4uGnBpnftf7ptLHsNr+VDxw0m8PPX8GRF6zgOVu3rBkNWu1TV/bS1gLH7DELgG3mBu5/91z++pa5nHHEHI7+yUqW9g6VwwVdgYVP5aIzT8QDwDdjh2hmlqHpdzbwROwQUj3porkPTdY/kBahY/aYxWt2m7Xm9K3nttDaEmgJgVP2mc2fHxq9E267SfrSvKCrhVc/s23My42UJAmfvLKXDz+/nY9d0cvHXtDOsXvO4gvXjT+g0DEr0DN+31qvk547mxvfMpcrT+hii47AzlsOvb18+6Y+LrlrFd99TceaNUztbYEtszVR+2zbyo7zWvjHE0OlrWdVQsesyRe0JlN2VGh6WYamWbVcXIZ7pZbW0hl6mvYjf5IknPTzHnbbqpX3Hrj2VNXDw9bLXHxHP7svWPcleHlfwlPZCMnyvoRL/znA7gsmNoX17b/1U9y5jXkdgRX90BLSrxXrWX6z21Yta7ZCm6zHlqfXv782yE/uWMWbdk9L4K/vXsXpV/Xx8zd20Dms3CxaPsjAYPpz3vPkIHctHuQZ89LHI0kSHlmWUNjcMgQ8hKNC086tyWbGF4D3AZvFDiLVg056m/Zd7qoHBjj/5n72WNDCXl9JN4v/9IvbednOs3j/73q56ZEBAlDYvIWvHpVuVbXwqUFO/nkPvzymk0eXJ7z6whUArBqEo3efxZHZOpuL7+jnnb/qYdGKhOL3VrDX01r4zbFdQLp4+tt/6+fSYzsBeO8Bs/n3i1YyuxW+/+8d42Yu7tzGV2/o5+Tnpt9/4bpe/veqPh5ZlrDnOct52c5tfOMVHTyybJB9v7acpb0JLQHOuraP298+l03bA/9+0UqeWJEu4P7yy+YwryP9Fb/jlyvpHYDDz09/pgO2b+UrR3Vw5X0DfOTydOqsNcBXinPYIrvODQ+nC7JHTrXlVJnumoevmWZhovug0MYplCqfBD4YO4dUD74761NXHNR626Gxc2jIwecu55KjO9l8TvwC8q5f9fCKXdt48TNy/3n9IWBHy9D0c5ps5pwJLF/vpaQc6Ai9vvbUmc8d0c79o2wBFsPuC1osQqnTLUIzwxekGVItF58gXUwt5d4c+uIPP2gt+2/fxp5bT37z+ql0yj6zY0eoB/eR7p5FM8AyNLM+BSyKHUKKrZ3++njXlerXf9Nda+7NLuuIZWgGVcvFGvCh2Dmk2NpDv6890tiupbv2/dgh8sQXpJn3DeCvsUNIMc2m3wUh0tjeGztA3liGZli1XBwETo2dQ4ppFgOWIWl0F9FduyZ2iLyxDEVQLRf/BPwgdg4pllmsmrX+S0m50wt8IHaIPLIMxfNfwIrYIaQYWhm0DEnr+jzdtWrsEHlkGYqkWi4+CJweO4cUQysDbjstrW0R6RbHisAyFNf/ke5LQsqVFhLLkLS2j9JdWxo7RF5ZhiKqlosrgdNi55BmWgtJ+/ovJeXGbcDXYofIM8tQZNVy8UfA5bFzSDMpWIak1RLgrXTXBmIHyTPLUH04FfAPQXkyJ3YAqU58g+7an2KHyDvLUB2olou34BCpcqKNVf0h4OE4JHgEeH/sELIM1ZMPA0/GDiFNtzn0ebwlKfVuumtLYoeQZahuZEe1/5/YOaTpZhmSAPgl3bULY4dQyjJUX74K/C52CGk6dYbevtgZpMiWA2+LHUJDLEN1pFouJsAJQC12Fmm6dGAZUu59hO6a+5irI5ahOpPtmdoDuappddLbHzuDFNGNwOdjh9DaLEN1qFoufge4OHYOaTo4TaYcGwBOcZ9C9ccyVL/eAjwWO4Q01broWRU7gxRJme7ajbFDaF2WoTpVLRcXkRYiqal0WoaUT9cD3bFDaHSWoTpWLRd/Cnwndg5pKnWFHqcIlDfLgWPprvlBoE5ZhurfqcADsUNIU8VpMuXQ++iu/SN2CI3NMlTnquViDTiR9GB+UsPrCit9LitPfkF37auxQ2h8lqEGUC0Xfwd8OXYOaSp00TsYO4M0Qx4FToodQutnGWocHwDuih1C2lid9DgypLw4ie7aotghtH6WoQZRLRdXAP+PdD8VUsPqCpYh5cI5dNcqsUNoYixDDaRaLl4LlGPnkDZGJ70hdgZpmt0JvC92CE2cZajxfBQP5qoG1kFv7AjSdFoBvJ7u2srYQTRxlqEGUy0XB4A3AtXIUaRJ6QiODKmpnUJ37ZbYIbRhLEMNqFouPgG8ivQTiNRQ5tDn646a1Rfprn0vdghtOF+UGlS1XPwbcErsHNKGarcMqTldheuEGpYvSg2sWi5+Dzgjdg5pQ7TT3xo7gzTFHgFeR3etP3YQTY5lqPG9H/h97BDSRM0Oq9piZ5Cm0CrgDXTXHo4dRJNnGWpwwxZU3xc7izQRs1nlyJCayfvprl0ZO4Q2jmWoCVTLxceBVwNuyqm618bArNgZpClyId21M2OH0MazDDWJarn4V+A/YueQ1scypCZxKx53rGlYhppItVy8APh87BzSeFoZnB07g7SRHgaKdNeWxw6iqWEZaj6nAZfHDiGNpcUypMa2HDiK7tr9sYNo6liGmky1XFwFvB7wD1V1qYWkPXYGaZLSDVa6azfGDqKpZRlqQtVycRHwCqAWO4s0UrAMqXGdSnftktghNPUsQ00q20P1UbiFmepPR+wA0iScQXft7NghND0sQ02sWi7+CXgd6U7BpOhaGVgVAu5nSI3mx6TrMdWkLENNrlouVoA3A0nkKBJz6OuJnUHaQNcCx9Fd8zW0iVmGcqBaLn4XODV2DskypAZzD/AKumsuN2hylqGcqJaLXwK6Y+dQvnWG3r7YGaQJegg4nO7aothBNP0sQzlSLRc/Bnwxdg7lVwe9vbEzSBPwGHAY3bV7YgfRzLAM5c+7gAtih1A+ddLbHzuDtB6LSUeE7owdRDPHMpQz1XIxAU4A3FeGZlxn6LEMqZ4tBY6ku3Zz7CCaWZahHBq2l+o/xs6ifOmkx908qF6tID3e2PWxg2jmWYZyqlourgReDtwUO4vyo8tpMtWnXuCVdNf+FDuI4rAM5Vi1XKwBLwHuip1F+dAVVg7EziCN0A+8lu7a72IHUTyWoZyrlouPAS8AboscRTnQRa9lSPVkADja443JMiSq5eJC4PnAn2NnUXPrCisHY2eQMv2kR6D/Uewgis8yJACq5eJi4MXAH2JnUfPqpMcypHrQA7zaIqTVLENao1ouLgNeBvwsdhY1py56PL6TYlsOHEV3rRI7iOqHZUhrqZaLvcBrgfNjZ1Hz6Qy9liHFtHo/Qr+PHUT1xTKkdWT7IToeD92hKdZJT4idQbmVbizi5vMahWVIo6qWi0m1XDwV+HjsLGoenXicVkVxP3AI3bW/xg6i+mQZ0riq5eJHgfcATm9oo3WEXkeGNNPuAA6iu/aP2EFUvyxDWq9quXgWcBLpPjmkSZtDn2VIM+k64Pl01x6MHUT1zTKkCamWi98iPZ6Z8xyatDn0tcbOoNy4iHSN0OOxg6j+WYY0YdVy8SdAkXTTVGmDzabf1xzNhE+T7lCxJ3YQNQZfmLRBquXi74CDgGrkKGpA7aG/LXYGNbV+4AS6ax+ku+Y6R02YZUgbrFou/g3YF/dWrQ00iwHLkKbLk8ARdNfOix1EjccypEmplotPAEcAZ8XOosYxi1WzYmdQU7obOIDu2uWxg6gxhSRxJFEbp1CqHAd8DZgTO4vq2+3tb/57Z+jbNXYONZU/kh5n7InYQdS4HBnSRquWi+cDBwMPxM6i+tbG4OzYGdRUvgMcZhHSxrIMaUpUy8UbSNcR/TF2FtWvFsuQpkYf8Da6a8fTXZvx3X2EED4YQrgthHBzCOGmEML+M51BU8sypClTLRcfA14MnB07i+pTC0l77AxqePcBB9NdOyfGnYcQDgSOAp6bJMmewGFM0ah4CMENDCKxDGlKVcvF/mq5+HbgZNxBo0YIliFtnF8Bz6W7dn3EDNsAjydJ0guQJMnjwPYhhJ8AhBBeGUJYGUKYHUKYE0K4Jzt9xxDCr0MIN4QQ/hhCeGZ2+nkhhDNCCJcB/xdCqIYQNl99ZyGEu0MIW4cQ5ocQfhxCuD77OmjGf/ImZhnStKiWi98EDgUejp1FdaUjdgA1pEHgo0CR7triyFkuBXYIIfwjhHB2COFQ4EZg7+z8Q4BbgecB+5MeEgTSjUzemSTJPsBprD2CvgtwWJIk7wF+BrwaIJt+qyZJ8ijweeDMJEmeB/w78I1p/BlzxyE5TZtquXhtoVTZB/gJcEDsPIqrhcGBEHzN0QZ7HDiG7tqlsYMAJEmyLISwD2npeSFwIVAC7g4h7AbsB5wBPB9oBf4YQpgL/BvwwxDWHJ5v+CjpD5MkWX3sxwuBjwDfAt6YfQ/pdNyzhl1/0xDCJkmSPDX1P2X+uGm9pl2hVJlNunv89wIeqDOnOlm5/PY5J3XFzqGGch3wOrprdbulagjhtcDxwPXAMtJDFr0ROI+0DJ0G3A/8PUmSbUa5/nnAJUmS/Cj7PgB3AQcCfwb2TZLkiRDC48AOSZKsnO6fKY+cJtO0q5aLfdVy8TTSnTQujJ1Hccyhz+NEaaIS4EzSI87XVREKIewaQth52El7kS7qvhJ4N3BNkiSLgC2BZwK3JUmyFLg3hPC67DZCCOE5o91+ko5QXEw6unRHkiSrdxtwKfCOYTn2mtqfLN8sQ5ox2XHN9iCdNlPOdIY+F9RrIh4g3XfQe2NsNj8Bc4FvhxBuDyHcDDwL6CYdxdqatBQB3AzcnAxNvxwDnBRC+BtwG/DKce7jQuBYhqbIAE4F9s02578deOsU/TzCaTJFUihVTiJdEOi0SU7sHB6s/rb9/YXYOVTXvgu8ne5aLXYQ5YsjQ4oi29psb9I5ceVAJ739sTOobi0GXk937ViLkGKwDCmaarl4F+kWFh/CfRI1vY7Q4yF0TrcAAAhGSURBVO9Yo/k1sAfdtR/GDqL8cjNXRVUtFweATxVKlZ8D32ZoXx1qMl30rIqdQXVlBXBarD1JS8M5MqS6UC0XbyHdQdnHAKdTmpDTZBrmWmBvi5DqhWVIdSM7lEc3aSm6NXIcTbG5YeVg7AyKrga8HTiI7to/YoeRVrMMqe5Uy8W/AvuQjhK5b5om0Umv02T5dhGwG921s+muWYxVVyxDqkvZjhq7gd1Id0CmBteFI0M5dS/wMrprb6C75rEKVZcsQ6pr1XKxWi0XX0O69+o7YufR5HWFHstQvqwCTgeeTXftV7HDSOOxDKkhVMvF3wLPAd4HLI0cR5PQRY97eM2Pq0kXSJfornksLdU9y5AaRrbA+gxgF9KDIPrm2kA6Q6+/r+b3OPAW4GC6a24EoYZhGVLDqZaLj1bLxRNId9j4l9h5NDGd9ITYGf5/e3cXKmldwHH8N+uysy9miCilZIOWlrW+EKbdlHYVTfRGEKwWCUZGIN0Ec9HLXHQxYAQiFIlRdKGYaYEMWWZkgW5a+VJt2aZO5ibuauuoLGdfPNvFM7tnN19W3XPOf+b8Px94mLMvF7/LL/M8z/+wZObS3BI7Pf3xtemPhS8zRQwxs0aD7uY0r+F/PsmOwnM4gnUOGV+J9ie5Psk7JrfE3MJmJokhZtpo0J0fDbrXpbl1dk2SFwpP4mWsa+0uPYHF9bskF6Q/viT98b9Kj4GjIYZYEUaD7jOjQffKJOcm+UXpPbzYuuw5pvQGFsXWJJ9If/z+9Mf3lh4Di0EMsaKMBt2/jAbdDyV5X5pfAMmUaGePZ4Zm29NJrkzzqvzPSo+BxdTav99zbqxcnd7wvUm+keTDpbfU7s41X9781lXbLyy9g9fs6STfTnJN+uPnSo+BpSCGqEKnNzw/ydeTfKT0llptbn/p3je1dp5fegev2o4k30rynfTHz5ceA0tJDFGVTm/4njRR9NHSW2rzx/YX7j+h9dy5pXdwRE8muSrJd9Mf7yo9BpaDGKJKnd7w3DRR9PEknmVZBg+2L//zca1dG0vv4GU9keasoGudGk1txBBV6/SG5yT5WpJPRhQtqS3tyx5a39p9ZukdvMjjaSLouvTHc6XHQAliCJJ0esONWYgir4AvgYfan32k3dp3WukdHLQ5ydVJbk5/vLf0GChJDMEhOr3hW9KcaH15kjcXnrOi/LN96bbVrflTSu+o3N4kNyW5Ov3xPaXHwLQQQ/ASOr3h6iQfS/LFJB+MW2hH7eH2JTuOae0/sfSOSu1I8r00D0X/p/QYmDZiCI6g0xuekeSKJJ9LcnzZNbPr0famZ1utHFd6R2UeSHMr7AbPA8HLE0PwKnV6w7VJPp3m26ILCs+ZOY+2N+1ptbKm9I4KzCW5Jc1bYXeWHgOzQAzB69DpDc9LE0WbkmwoPGfqtTI//+jaS/36n6X1pyTfT3J9+uNnSo+BWSKG4Ch0esPjknwmTRi9q/CcqbUuu3f9be1l60vvWIG2J7khyQ/TH99fegzMKjEEi6TTG56d5FOT652F50yV4/PszvvWXuF5q8Uxl+TWJD9Kclv6432F98DME0OwBDq94VlZCKPqT10+OU89cdfaKx1V8PrtTvKrJDcn+anbYLC4xBAsscnbaAfC6LzCc4o4vbXtsTvaXzm19I4Z83ySn6d5GHroN8bD0hFDsIw6veFpWQijan6D+8bWI1tvbX/17aV3zID/prkFdkuSX3odHpaHGIJCOr3hqVkIowuzgg92vKC1ZcuN7W+eVXrHlBpl4Rug33gGCJafGIIp0OkNT0zygSQXTa6zsoLi6OJV9z3wgzVXnVN6x5TYmeTXaZ4Buj398cOF90D1VpceACSjQXdHkp9MrgNxdFEOj6OZtSFzL5TeUNCeJHcluT1NAP0h/fF82UnAocQQTKFJHN00udLpDU9K883RxWniaKZe3V/fmqvp1s9cmgMQ70pyR5Lfpj/eVXYS8ErEEMyA0aC7PS+Oo4sm18VJzswU31Y7duV+M7Q/ydYkv0+yefL5YPrjvUVXAa+JGIIZNImjH0+udHrDNyR5d5Kz05xrdOCaioMO16+cGHoqyb1ZCJ970h/vLDsJOFpiCFaA0aD7XJK7J9dBnd7wlBweRxvT3GJrL+e+Da25WXtT46kkf02yZXI1P/fHTxZdBSwJMQQr2GjQ3ZZkW5LbDvxdpzdcneSMHB5Ib0tySpI3LsWODZmbxgeGdyd5PM2r7X/P4dGzo+AuYJmJIajMaNDdl4VvPG489N86veH6NFF08it8npzX+M3Shtaynx04n+TJJI9Nrn+/xOf29Mez9o0VsATEEHDQaNDdleaB4K2v9P86veEJOTySTkpybJINh1wH/7wq808k+UeSNf93tZLsm1x7j/A5l+aMnp1Jnjnk55e+HF4IvEoOXQQAqraq9AAAgJLEEABQNTEEAFRNDAEAVRNDAEDVxBAAUDUxBABUTQwBAFUTQwBA1cQQAFA1MQQAVE0MAQBVE0MAQNXEEABQNTEEAFRNDAEAVRNDAEDVxBAAUDUxBABUTQwBAFUTQwBA1cQQAFA1MQQAVE0MAQBVE0MAQNXEEABQNTEEAFRNDAEAVRNDAEDVxBAAUDUxBABUTQwBAFUTQwBA1cQQAFA1MQQAVE0MAQBVE0MAQNXEEABQNTEEAFRNDAEAVRNDAEDVxBAAUDUxBABUTQwBAFUTQwBA1cQQAFA1MQQAVE0MAQBVE0MAQNXEEABQNTEEAFRNDAEAVRNDAEDVxBAAUDUxBABUTQwBAFUTQwBA1cQQAFA1MQQAVE0MAQBVE0MAQNXEEABQNTEEAFRNDAEAVfsfZJ4fMQE9efYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x92a2748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset['Is Swerve'] = dataset.apply(lambda r: 'swerve' in r['Folder'], axis=1)\n",
    "grouped = dataset.groupby(by=['Is Swerve']).size().reset_index()\n",
    "grouped.columns = ['Is Swerve', 'Count']\n",
    "\n",
    "def make_autopct(values):\n",
    "    def my_autopct(percent):\n",
    "        total = sum(values)\n",
    "        val = int(round(percent*total/100.0))\n",
    "        return '{0:.2f}%  ({1:d})'.format(percent,val)\n",
    "    return my_autopct\n",
    "\n",
    "pie_labels = ['Normal', 'Swerve']\n",
    "fig, ax = plt.subplots(figsize=FIGURE_SIZE)\n",
    "ax.pie(grouped['Count'], labels=pie_labels, autopct = make_autopct(grouped['Count']))\n",
    "plt.title('Number of data points per driving strategy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, roughly a quarter of the data points are collected with the swerving driving strategy, and the rest are collected with the normal strategy. We also see that we have almost 47,000 data points to work with. This is nearly not enough data, hence our network cannot be too deep. \n",
    "\n",
    "> **Thought Exercise 0.4:**\n",
    "Like many things in the field of Machine Learning, the ideal ratio of number of datapoints in each category here is something that is problem specific, and can only be optimized by trial and error. Can you find a split that works better than ours?\n",
    "\n",
    "Let's see what the distribution of labels looks like for the two strategies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9203e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9218588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(-1, 1.05, 0.05)\n",
    "normal_labels = dataset[dataset['Is Swerve'] == False]['Steering']\n",
    "swerve_labels = dataset[dataset['Is Swerve'] == True]['Steering']\n",
    "\n",
    "def steering_histogram(hist_labels, title, color):\n",
    "    plt.figure(figsize=FIGURE_SIZE)\n",
    "    n, b, p = plt.hist(hist_labels.as_matrix(), bins, normed=1, facecolor=color)\n",
    "    plt.xlabel('Steering Angle')\n",
    "    plt.ylabel('Normalized Frequency')\n",
    "    plt.title(title)\n",
    "    plt.show()\n",
    "\n",
    "steering_histogram(normal_labels, 'Normal label distribution', 'g')\n",
    "steering_histogram(swerve_labels, 'Swerve label distribution', 'r')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a few observations we can make about the data from these plots:\n",
    "* **When driving the car normally, the steering angle is almost always zero**. There is a heavy imbalance and if this portion of the data is not downsampled, the model will always predict zero, and the car will not be able to turn.\n",
    "* When driving the car with the swerve strategy, we get examples of sharp turns that don't appear in the normal strategy dataset. **This validates our reasoning behind collecting this data as explained above.** \n",
    "\n",
    "At this point, we need to combine the raw data into compressed data files suitable for training. Here, we will use .h5 files, as this format is ideal for supporting large datasets without reading everything into memory all at once. It also works seamlessly with Keras.\n",
    "\n",
    "The code for cooking the dataset is straightforward, but long. When it terminates, the final dataset will have 4 parts:\n",
    "\n",
    "* **image**: a numpy array containing the image data\n",
    "* **previous_state**: a numpy array containing the last known state of the car. This is a (steering, throttle, brake, speed) tuple\n",
    "* **label**: a numpy array containing the steering angles that we wish to predict (normalized on the range -1..1)\n",
    "* **metadata**: a numpy array containing metadata about the files (which folder they came from, etc)\n",
    "\n",
    "The processing may take some time. We will also combine all the datasets into one and then split it into train/test/validation datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data from data_raw/normal_1...\n",
      "Reading data from data_raw/normal_2...\n",
      "Reading data from data_raw/normal_3...\n",
      "Reading data from data_raw/normal_4...\n",
      "Reading data from data_raw/normal_5...\n",
      "Reading data from data_raw/normal_6...\n",
      "Reading data from data_raw/swerve_1...\n",
      "Reading data from data_raw/swerve_2...\n",
      "Reading data from data_raw/swerve_3...\n",
      "Processing data_cooked/train.h5...\n",
      "Finished saving data_cooked/train.h5.\n",
      "Processing data_cooked/eval.h5...\n",
      "Finished saving data_cooked/eval.h5.\n",
      "Processing data_cooked/test.h5...\n",
      "Finished saving data_cooked/test.h5.\n"
     ]
    }
   ],
   "source": [
    "train_eval_test_split = [0.7, 0.2, 0.1]\n",
    "full_path_raw_folders = [os.path.join(RAW_DATA_DIR, f) for f in DATA_FOLDERS]\n",
    "Cooking.cook(full_path_raw_folders, COOKED_DATA_DIR, train_eval_test_split)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "We are now ready to start building our model. Head over to the [next notebook](TrainModel.ipynb) to begin."
   ]
  }
 ],
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